Philippine E-Journals

UNDERSTANDING THE PATTERNS OF LIBRARY USAGE AND COLLECTION USAGE AMONG UNDERGRADUATE STUDENTS OF N.U.-MANILA: A MACHINE LEARNING APPROACH

Editha A. Alamodin | Mideth B. Abisado | Ramon L. Rodriguez | Bernie S. Fabito

 

Abstract:

Purpose/Objectives: This study aimed to explore and understand library usage and collection usage among National University undergraduate students, per discipline, in the last two academic years (AY 2015-2016 and AY2016-2017), through manual library usage statistics, system-generated data from Follett’s Destiny Library Manager (DLM) for the book collection usage, and ProQuest Usage for electronic journal databases. Based on the generated data, patterns of library usage and collection usage were identified, specifically: (1) the relationship of library collection usage vis-à-vis student degree program; (2) library usage trends in terms of academic month; and (3) sufficiency of library collection. Significance of the study: This study provides valid statistics and research data useful to the NU Administrative body and NU-LRC as basis for planning and improvement of library collection and services. Identification of appropriate book collection titles and electronic journal databases will increase student library usage. Knowing the relationship between student degree program and student usage can help in identifying which library collection per program has sufficient collection. The user patterns will also determine if the current collection addresses the actual LRC information resource needs of each student; and can therefore serve as justification for purchase requests for current, new, and relevant additional books and other electronic journal databases for subscription. Library user patterns can also inform planning for a more effective or better utilization of library sources and services in the NU community. Design, methodology, and approach: The study used simple machine learning and statistical techniques to achieve its goals. The data were obtained from library usage statistics, NU-LRC library system, Follett’s Destiny Library Manager for book usage, and ProQuest usage for e journal databases from AY 2015-2016 to AY 2016-2017. Statistical analysis was employed to show the pattern of library usage at National University-Manila. The cleaned data were processed using data tools in MS Excel to understand the usage of library resources from AY 2015-2016 to AY 2016-2017. Pattern analysis was based on the results of the statistical analysis. Visualization techniques were used to understand the usage pattern of the students. Findings: The results of the study are presented and discussed with reference to the goal of the study, which is to understand the library usage and collection usage patterns of the students of National University-Manila. Students were found to utilize books related to their field of specialization, for instance, 90% of nursing students as well as architecture and dentistry students were using resources related to their respective fields of study. The result shows consistency of book collection usage per college for both academic years. No consistency was noted in the growth or decline in the number of library users for the two academic years. The highest number of library users was found in the College of Business and Accountancy in AY 2015-2016, and in the College of Tourism and Hospitality Management in AY 2016-2017. In terms of library usage per month, most students borrowed/used library collections or visited the library for their academic needs during the middle of the semester, which was the period of examinations at the university. In June, October, April, and May, the number of library users was expectedly low across colleges, since these months were either the start or the end of the semester. The library user behavior notably changed because of the students’ access to technology. Some of them opted to use online materials or resources rather than library book collections. The visualized data in graph form indicate that the students mostly used 2003-2012 editions of books, since these editions were greater in number than the recent ones. Research limitations and implications: The study initially intended to use machine-learning techniques to develop a model for understanding library usage at the university, but data from the library were not enough for building the model. Since the covered period was limited only to two academic years (AY 2015-2016, AY 2016-2017), the results could not be generalized and could not provide any correlation between library usage and collection usage pattern. Originality of the paper: Related literature in the local setting was limited. The data gathered were analyzed and machine learning and statistical techniques were employed to determine the significance between library usage and collection usage.